- Adding ability to use native spark row writing for bulk_insert
- Controlled by `ENABLE_ROW_WRITER_OPT_KEY` datasource write option
- Introduced KeyGeneratorInterface in hudi-client, moved KeyGenerator back to hudi-spark
- Simplified the new API additions to just two new methods : getRecordKey(row), getPartitionPath(row)
- Fixed all built-in key generators with new APIs
- Made the field position map lazily created upon the first call to row based apis
- Implemented native row based key generators for CustomKeyGenerator
- Fixed all the tests, with these new APIs
Co-authored-by: Balaji Varadarajan <varadarb@uber.com>
Co-authored-by: Vinoth Chandar <vinoth@apache.org>
- Consolidate transform functions for tests in Transformations.java
- Consolidate assertion functions for tests in Assertions.java
- Make use of SchemaTestUtil for loading schema from resource
- Storage Type replaced with Table Type (remaining instances)
- View types replaced with query types;
- ReadOptimized view referred as Snapshot Query
- TableFileSystemView sub interfaces renamed to BaseFileOnly and Slice Views
- HoodieDataFile renamed to HoodieBaseFile
- Hive Sync tool will register RO tables for MOR with a `_ro` suffix
- Datasource/Deltastreamer options renamed accordingly
- Support fallback to old config values as well, so migration is painless
- Config for controlling _ro suffix addition
- Renaming DataFile to BaseFile across DTOs, HoodieFileSlice and AbstractTableFileSystemView
- Upgrade Spark to 2.4.4, Parquet to 1.10.1, Avro to 1.8.2
- Remove spark-avro from hudi-spark-bundle. Users need to provide --packages org.apache.spark:spark-avro:2.4.4 when running spark-shell or spark-submit
- Replace com.databricks:spark-avro with org.apache.spark:spark-avro
- Shade avro in hudi-hadoop-mr-bundle to make sure it does not conflict with hive's avro version.
- Docs were talking about storage types before, cWiki moved to "Table"
- Most of code already has HoodieTable, HoodieTableMetaClient - correct naming
- Replacing renaming use of dataset across code/comments
- Few usages in comments and use of Spark SQL DataSet remain unscathed
- Add spotless format fixing to project
- One time reformatting for conformity
- Build fails for formatting changes and mvn spotless:apply autofixes them
